While other models present methodologies for a top-down approach to innovation, the EIT methodology focuses on a bottom-up approach of optimizing existing people, processes, and technologies to produce a highly efficient model of interoperability.
A featured component of this model is data liquidity and migration, which represents a fluid data structure free from closed architectures or "siloed data" scenarios to provide enterprise-wide accessibility and flexibility. However, this methodology requires that imaging data be accurately and cleanly migrated to an enterprise platform for storage.
To further understand the "why" of migration scenarios, we've identified three of the larger forces fueling imaging transformation in healthcare, which are discussed below.
Mergers and acquisitions
Creating economies of scale, work standards, and efficient utilization of resources across healthcare enterprises is critical for organizations that focus on profitability and want to extend services, without duplication, to the outer reaches of their enterprise. Mergers and acquisitions (M&A) may result in a multitude of disparate platforms and methodologies for image storage which increase the complexity required to create a seamless and centralized image distribution environment.
Without a centralized imaging platform, access to clinically relevant imaging data may become difficult or impossible with the expansion of enterprise clinical services. For example, an acute care organization may acquire additional imaging centers to enhance professional services and subspecialty capacity for the overall clinical service line. This scenario requires not only that the imaging center have access to the organization's existing enterprise data, but also that clinically relevant historical data are freed from proprietary or closed architecture.
To achieve this, a strategic migration effort must be implemented to free data from disparate containers and make information available to the greater enterprise. Although there are cases where maintaining siloed architecture may be desirable, image access between facilities will remain autonomous and cumbersome.
Enterprise imaging consolidation
Similar to M&A scenarios, enterprise imaging consolidation recompiles siloed data within a central and vendor-neutral platform to drive economies of scale, unify work standards, and optimize reimbursement opportunities. Cost drivers such as capital expense and continued support and maintenance of duplicate platforms weigh heavily on an organization's bottom line. Organizations looking to take full advantage of their technical and professional services across the entire enterprise must take consolidating imaging data to the furthest logical footprint of their organization.
These consolidations may include not only acute facility consolidation, but also ambulatory outpatient and group practice settings. For example, organizations creating "centers of excellence" may house specialty physicians, such as pediatric radiologists, in a centralized location far from the source of image acquisition and point-of-care physicians. To enable this method of specialty care, organizations must implement an enterprise imaging strategy. Once again, these disparate entities present great challenges for consolidation, which requires migration strategies to recompile clinically relevant historical data within a central repository.
Replacement and cost avoidance
While M&As and enterprise consolidations are clear drivers for standardizing technology, the cost of equipment replacement is also important, with considerations such as end-of-life (EOL) hardware storage platforms. Advances in tiered storage methodologies, the ever-decreasing costs of disk space, and a more flexible attitude toward healthcare-based cloud storage means infrastructure teams are presented with a variety of platform options for mitigating costs and improving accessibility.
Strategic migration methodology
As seen in the previous three scenarios, strategic migrations are critical for decoupling and standardizing data ingested by a new enterprise system. The effect of a migration is clean imaging datasets, unadulterated by proprietary tagging and manipulations, that provide "liquidity" and consistency across all imaging content.
Considering that every image in an organization must be touched during a migration, a complete implementation process/methodology should account for the duration of the migration process while systems churn through the organization's repositories. This process can take weeks, months, or years depending on disparity and quantity of systems, storage technologies, and image life-cycle management (ILM) initiatives.
Understanding the essentials for establishing data liquidity will help department managers and project leaders plan for accessing data pre- and postmigration as individual systems migrate into a single robust repository. In addition, other imaging initiatives may be underway during a vendor-neutral archive (VNA) implementation such as consolidation of other "-ologies" and implementation of enterprise diagnostic viewers (EDVs) to expand a department's imaging capabilities. Both the current and future imaging viewers and data visualization tools must know where to identify the source of truth for imaging data information during data migration.
Image complexity also weighs heavily on migration strategies and timelines. Specialized imaging continues to grow and increase in complexity. Complex datasets such as volume rendering and digital breast tomosynthesis can be tricky with standards and archives. Proprietary tagging, accession number issues, and image object change management are just a few of the many issues to consider when analyzing an organization's current imaging architecture, all of which must be strategically addressed to provide true imaging data liquidity and interoperability across the enterprise imaging platform.
Utilizing a robust migration strategy as a focused strategic initiative can ensure that complex imaging datasets are standardized accordingly and with flexibility to handle the ever-changing landscape of healthcare technology.
The migration process1
Although an organization's technical systems and vendor implementation processes can vary, a migration initiative can be viewed as a phased process from setup to tear-down. Working with a phased structure allows administrators to run parallel efforts in conjunction with other initiatives driving an imaging transformation.
An example of a four-phase initiative demonstrates activities occurring from contract signature to tear-down of the migration system:
- System setup. During the system setup phase, a server is configured, shipped, racked, and integrated with the client's network. Connectivity is tested between the legacy image repository and the test and production systems.
- Inventory validation and training. The inventory validation and training phase begins with a deep assessment of the legacy system architecture and user interface training for Web administration.
- Data extraction and migration. During the data extraction and migration phase, sample study data are extracted from legacy systems and sent to the test server and production servers. Sample study data are validated and migration is started.
- Cleanup and closure. During cleanup and closure, outstanding issues are compiled, reported, and reconciled. Migration to the new target is complete, the project is closed out, and hardware is returned to the vendor.
A strategic migration strategy is a critical part of any organization's imaging platform transformation and should not be overlooked. Results of a migration can greatly influence the liquidity of image data for current and future system initiatives.
Whether approaching a PACS replacement, VNA initiative, consolidation, workflow manager implementation, or enterprise analytics, consistent imaging data are an integral component of the success of imaging initiatives. A migration should be approached diligently, resourced accordingly, and ideally carried out at the forefront of an enterprise imaging transformation initiative to provide optimum results.
- Data Migration Process per Laitek
Dave Whitney is a senior consultant at Ascendian Healthcare Consulting and a frequent contributor to the subject of health information technology and enterprise imaging transformation. You may contact him directly at firstname.lastname@example.org or visit the Ascendian website for more information.
The comments and observations expressed herein do not necessarily reflect the opinions of AuntMinnie.com.
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